[go: up one dir, main page]

Wu et al., 2016 - Google Patents

Automatic liver segmentation on volumetric CT images using supervoxel‐based graph cuts

Wu et al., 2016

View PDF @Full View
Document ID
421915285356045837
Author
Wu W
Zhou Z
Wu S
Zhang Y
Publication year
Publication venue
Computational and mathematical methods in medicine

External Links

Snippet

Accurate segmentation of liver from abdominal CT scans is critical for computer‐assisted diagnosis and therapy. Despite many years of research, automatic liver segmentation remains a challenging task. In this paper, a novel method was proposed for automatic …
Continue reading at onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10088—Magnetic resonance imaging [MRI]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30056—Liver; Hepatic
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30048—Heart; Cardiac
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G06T2207/20156—Automatic seed setting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10104—Positron emission tomography [PET]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20101—Interactive definition of point of interest, landmark or seed
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05—Recognition of patterns in medical or anatomical images

Similar Documents

Publication Publication Date Title
Wu et al. Automatic liver segmentation on volumetric CT images using supervoxel‐based graph cuts
Moghbel et al. Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
Wu et al. 3D liver tumor segmentation in CT images using improved fuzzy C‐means and graph cuts
Scalco et al. Texture analysis of medical images for radiotherapy applications
Linguraru et al. Tumor burden analysis on computed tomography by automated liver and tumor segmentation
Lu et al. Fully automatic liver segmentation combining multi-dimensional graph cut with shape information in 3D CT images
US9990712B2 (en) Organ detection and segmentation
Esneault et al. Liver vessels segmentation using a hybrid geometrical moments/graph cuts method
Abd-Elaziz et al. Liver tumors segmentation from abdominal CT images using region growing and morphological processing
Banerjee et al. Single seed delineation of brain tumor using multi-thresholding
Yang et al. Semi-automatic liver tumor segmentation with adaptive region growing and graph cuts
Alirr et al. Survey on liver tumour resection planning system: steps, techniques, and parameters
CN114830174A (en) Image analysis system for identifying lung features
Ballangan et al. Lung tumor segmentation in PET images using graph cuts
Memon et al. Segmentation of lungs from CT scan images for early diagnosis of lung cancer
López-Mir et al. Liver segmentation in MRI: A fully automatic method based on stochastic partitions
Wang et al. A new segmentation framework based on sparse shape composition in liver surgery planning system
Dakua Performance divergence with data discrepancy: a review
Cha et al. Segmentation and tracking of lung nodules via graph‐cuts incorporating shape prior and motion from 4D CT
Huang et al. Automatic Liver Segmentation from CT Images Using Single‐Block Linear Detection
Cui et al. Topology polymorphism graph for lung tumor segmentation in PET-CT images
Alirr et al. An automated liver tumour segmentation from abdominal CT scans for hepatic surgical planning
JP6415878B2 (en) Image processing apparatus, image processing method, and medical image diagnostic apparatus
Tan et al. An approach for pulmonary vascular extraction from chest CT images
Chen et al. Functional region annotation of liver CT image based on vascular tree